WISAN testing on a bridge

The bridge (Figure 1(a)(b)) was tested in 2 setups using 44 sensors in on two girders and four girders respectively. The sensors were clamped on the bottom of the girders to provide a clear line-of-sight to the PAN Coordinator station (Figure 2) placed under the bridge on the bottom left of the entire setup. The PAN Coordinator station consisted of 6 PAN Coordinators connected to a laptop via serial interface. GPS was used to provide pulse per second synchronization signal to the PAN Coordinators. TCP based server was used to send / receive data from the network. LabView based client application was used to control the data collection process. The network configuration for the tests is shown in Figure 3.

The sensors formed six network clusters on six independent frequency channels that synchronized within ±23 µs using a synchronizing signal provided by the GPS receiver. Acceleration data was sampled at the rate of 240.385 Hz and a data resolution of 14 bits. Traffic passing over the bridge was the source of bridge excitation. Number of data recordings for the three setups were taken for 30 seconds, 2 minutes, 5 minutes and 10 minutes were taken. The cut of frequency of the programmable filter was varied between 100 Hz and 40 Hz to filter out high frequency noise components. Figure 4 shows a time series data for a sensor located near the center of the second girder. The frequency spectrum of the data shows peak amplitude of around 25 mg in the range of 8 – 12 Hz. This corresponds to roughly 6% of the total resolution of the ADC and which is approximately only 6 bits of sensor resolution which is much lower to that seen from the bridge on Route 11 in Potsdam.

(a) (b)

Figure 1: Different views of the bridge on Chipman Road

(a)

(b)

(c)

Figure 2: (a) Placement of WISAN sensors under the bridge (b) PAN Coordinator Station (c) Wireless Sensor clamped to the girder on the bridge

Figure 3: Network configuration for bridge testing (click to enlarge)

Figure 4: (a) Acceleration data from sensor located near the center of second girder. (b) Frequency spectrum of data from sensor located near the center of second girder.

Four Girder Grid Setup

In the first setup, all four girders were equipped with 11 sensors each. The layout of the test setup is shown in Figure 5.

Figure 5: Layout of the bridge test setup for the four girder grid setup

The data collected from all the sensors was processed using the output-output modal analysis software ARTeMIS. Mode shapes from the four girder grid setup were successfully identified as summarized in Table 1 and shown in Figure 6 – Figure 10.

Mode Number

Frequency (Hz)

1

9.155

2

32.75

3

53.65

Table 1 (a): Vibration modal frequencies along the length of the bridge

Mode Number

Frequency (Hz)

1

10.97

2

26.23

Table 1 (b): Vibration modal frequencies along the width of the bridge

Figure 6: Three dimensional view of the first mode at 9.155 Hz obtained along the length of the bridge for four girder grid setup

Figure 7: Three dimensional view of the second mode at 32.75 Hz obtained from four girder grid setup

Figure 8: Three dimensional view of the third mode obtained at 53.65 Hz obtained from four girder grid setup

Figure 9: Three dimensional views of the first mode at 10.97 Hz obtained along the width of the bridge (side mode)

Figure 10: Three dimensional view of the second mode at 26.23 Hz obtained along the width of the bridge

Two girder grid setup

In the second setup, first two girders were equipped with 22 sensors each as shown in Figure 11. The mode shapes obtained are shown in Figure 12 to Figure 15.

Figure 11: Layout of the bridge test setup for the two girder grid setup

Figure 12: Three dimensional view of the 1st longitudinal modes identified at 9.155 Hz using the two girder grid setup.

Figure 13: Three dimensional view of the 2nd side modes identified at 26.23 Hz using the two girder grid setup.

Field test on RT11 bridge

Identification of natural frequencies, and range of accelerations and displacements from ambient excitation

Vibration data were acquired using a custom made sensor module that interfaced a MEMSIC MXR2999 and an Applied MEMS SF1500S acceleration sensors. The output of each sensor was buffered and connected to the 12-bit ADC of a WISAN node and to a 16-bit USB data acquisition system. Data acquisition software was written in Labview and supported simultaneous data acquisition from the wireless and wired interfaces at 100Hz sampling rate.

The following figures show the sensor module and Labview interface.

Two sensor modules were placed on the overpass bridge over Raquette river on RT11 in Potsdam, NY. The temperature during the test was about 32F or 0C. The bridge was excited by passing traffic.

Both sensors were attached on the girder number 4 under the deck. One of the sensor boxes was attached in the close proximity of the support column, while another sensor box was attached at various locations.

Sensor location close to a support column.

First sensor location. Midspan of the girder

First sensor location. Midspan of the girder.

Second sensor location: Moving closer to the support.

Third sensor location

Some results

Test has shown very good correlation between wired and wireless data. The slight difference in results is caused by sample-to-sample asyncronization on the order of 10ms.

Wired data from Applied MEMS sensor (normalized by average)

Wireless data from the same sensor

Overplot of wireless and wired data shows good visual match between time series

Cross-correlation function of the time domain wired and wireless series clearly indicates a single point of the best match between series.

Power spectral density of the wired time series

Power spectral density of the wireless time series

Overplot of the frequency data indicates very good match in in the 10Hz frequency band.

The cross-correlation function in the frequency domain is almost identical to the cross-correlation function in time domain and indicates a single point of best match between the wired and wireless data